A probabilistic deep reinforcement learning approach for optimal monitoring of a building adjacent to deep excavation
| Autor(en): |
Yue Pan
(State Key Laboratory of Ocean Engineering Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure School of Naval Architecture, Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China)
Jianjun Qin (State Key Laboratory of Ocean Engineering Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure School of Naval Architecture, Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China) Limao Zhang (School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan Hubei China) Weiqiang Pan (Shanghai Tunnel Engineering Co., Ltd. Shanghai China) Jin‐Jian Chen (State Key Laboratory of Ocean Engineering Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure School of Naval Architecture, Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China) |
|---|---|
| Medium: | Fachartikel |
| Sprache(n): | Englisch |
| Veröffentlicht in: | Computer-Aided Civil and Infrastructure Engineering, Februar 2024, n. 5, v. 39 |
| Seite(n): | 656-678 |
| DOI: | 10.1111/mice.13021 |
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Datenseite - Reference-ID
10725630 - Veröffentlicht am:
30.05.2023 - Geändert am:
20.09.2024
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